A Machine Learning Approach to Support Urgent Stroke Triage Using Administrative Data and Social Determinants of Health at Hospital Presentation: Retrospective Study.
Min ChenXuan TanRema PadmanPublished in: Journal of medical Internet research (2023)
Using data widely available at the time of patients' hospital presentations, we developed a stroke prediction model with high sensitivity and reasonable specificity. The prediction algorithm uses variables that are routinely collected by providers and payers and might be useful in underresourced hospitals with limited availability of sensitive diagnostic tools or incomplete data-gathering capabilities.
Keyphrases
- machine learning
- healthcare
- big data
- electronic health record
- end stage renal disease
- atrial fibrillation
- emergency department
- newly diagnosed
- public health
- chronic kidney disease
- artificial intelligence
- deep learning
- peritoneal dialysis
- prognostic factors
- mental health
- risk assessment
- blood brain barrier
- neural network
- structural basis